School of Health, Glasgow Caledonian University, Glasgow, UK.
Diabet Med. 2010 Feb;27(2):162-8. doi: 10.1111/j.1464-5491.2009.02914.x.
Older people with diabetes mellitus (DM) may be at high risk of falling because of general risk factors for falls as well as disease-specific factors.
To determine the prevalence of falls and to investigate lower-limb factors for falls in older people with DM. Methods Sixty patients with DM over 55 years of age were recruited. 'Fallers' were those who self-reported at least one fall in the previous year. In addition to diabetes status and demographic information, the following were assessed: neuropathy symptom score (NSS), neuropathy disability score (NDS), foot deformity score (FDS), Tinetti performance-oriented assessment of mobility (POMA), ankle muscle strength and gait parameters. Data from 'fallers' and 'non-fallers' were compared and logistic regression analysis performed to identify variables predictive of falls.
Thirty-five per cent (n = 21) of participants had fallen in the preceding year. Compared with 'non-fallers', there was a greater incidence of peripheral neuropathy among 'fallers' (86% of 'fallers' and 56% of 'non-fallers'), higher vibration perception threshold (P = 0.04), slower gait velocity (P < 0.001), lower muscle strength for dorsiflexion, plantarflexion, inversion and eversion (all P < 0.001) and higher incidence of bony prominences and prominent metatarsal heads (both P < 0.001). There was a strong and significant correlation between dorsiflexion muscle strength and gait velocity. Logistic regression analysis determined that walking velocity, strength of ankle dorsiflexors and NSS accurately predicted 75% of 'fallers'.
Simple clinical measures of gait velocity and ankle muscle strength may be used to identify people with DM at risk of falling, allowing preventative strategies to be implemented.
患有糖尿病(DM)的老年人由于一般的跌倒风险因素和特定于疾病的因素,可能面临较高的跌倒风险。
确定老年人中 DM 患者的跌倒发生率,并研究下肢与跌倒相关的因素。
共招募了 60 名年龄在 55 岁以上的 DM 患者。“跌倒者”是指在过去一年中至少报告过一次跌倒的患者。除了糖尿病状况和人口统计学信息外,还评估了以下内容:神经病变症状评分(NSS)、神经病变残疾评分(NDS)、足部畸形评分(FDS)、Tinetti 以动作为导向的移动能力评估(POMA)、踝部肌肉力量和步态参数。将“跌倒者”和“非跌倒者”的数据进行比较,并进行逻辑回归分析,以确定预测跌倒的变量。
35%(n=21)的参与者在过去一年中跌倒过。与“非跌倒者”相比,“跌倒者”中周围神经病变的发生率更高(86%的“跌倒者”和 56%的“非跌倒者”),振动觉阈值更高(P=0.04),步态速度更慢(P<0.001),背屈、跖屈、内翻和外翻的肌肉力量更低(均 P<0.001),以及骨隆起和突出的跖骨头的发生率更高(均 P<0.001)。背屈肌肉力量与步态速度之间存在强而显著的相关性。逻辑回归分析确定,步态速度、踝关节背屈肌力量和 NSS 可准确预测 75%的“跌倒者”。
简单的临床步态速度和踝部肌肉力量测量方法可用于识别有跌倒风险的 DM 患者,从而实施预防策略。